The use of multiple antennas at both the transmitter and receiver ends, commonly known as Multiple Input Multiple Output (MIMO), is now widespread in Fourth Generation (4G) wireless communication applications. MIMO allows large improvements in spectral efficiency, cell capacity, and user throughput. MIMO exploits multipath on the channel to yield the capacity improvements.
One particular MIMO scheme is called Spatial Multiplexing (SM). With SM, independent streams of data are transmitted from each antenna using the same time and frequency resource. In an Orthogonal Frequency Division Multiplexing (OFDM) system, for instance, independent symbols are transmitted from each antenna in the same OFDM symbol and the same subcarrier location. The streams of data combine in the air, interfering with each other. The symbols are received on multiple receive antennas and are then processed in a MIMO decoder. A MIMO decoder is a signal processing device that separates the independent streams of data.
Standard Maximum Likelihood Decoding (MLD) is currently an optimal detector in terms of its ability to successfully determine what symbols were transmitted in the different streams. The problem with standard MLD is that it is very complex and moreover the complexity grows exponentially with the number of antennas and the modulation order (as MNt where M is the modulation order and NT is the number of Transmit antennas).
Sphere decoding is an algorithm that achieves the performance of MLD at a reduced complexity. In sphere decoding, a sphere is defined about the received point and potential solutions that fall outside of the sphere are eliminated. A QR decomposition is first performed on the channel matrix H, after some mathematical manipulation, the Q matrix is then multiplied by the received point to obtain a transformed received point. The spheres are defined about the transformed received point. The potential solutions are the actual transmitted constellation points scaled by the R matrix. It considers one dimension at a time, I of Tx antenna 1, Q of Tx antenna 1, I of Tx antenna 2 and Q of Tx antenna 2.
The problem with such decoders is that their complexity requires a significant power consumption and processing time.
There is a need for a decoder that retains a performance which is very reliable but with a fraction of the complexity in order to reduce power consumption and processing time.
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